Systems and methods for a self-adjusting node workspace

- MAXON COMPUTER GMBH

Systems and methods are disclosed for automatically adjusting a workspace comprising a plurality of nodes for sustained workflow. One method comprises receiving a new node in the workspace and determining that the new node overlaps with one or more nodes. Based on the determination, a set of nodes within a predetermined distance of the overlap may be repositioned, the set of nodes comprising the new node and the one or more nodes. Upon determining that the new node still overlaps with the one or more nodes, the set of nodes may be scaled down until there is no overlap.

Skip to: Description  ·  Claims  ·  References Cited  · Patent History  ·  Patent History
Description
TECHNICAL FIELD

The present disclosure relates to systems and methods for three-dimensional modeling process enhancement. More particularly, the present disclosure relates to systems and methods for adjusting placement and scaling of nodes in a workspace of a node editor.

BACKGROUND

In three-dimensional (3D) modeling, a node editor allows a user to create an object by routing basic properties through a set of nodes. Each node may perform an operation on the properties, changing how the object will appear visually in 3D space, and may pass the modified properties to the next node. By utilizing various nodes and making appropriate connections between them, desired object appearances can be achieved.

The background description provided herein is for the purpose of generally presenting the context of the disclosure. Unless otherwise indicated herein, the materials described in this section are not prior art and are not admitted to be prior art, or suggestions of the prior art, by inclusion in this section.

SUMMARY OF THE DISCLOSURE

One embodiment provides a computer-implemented method of automatically adjusting a workspace comprising a plurality of nodes for sustained workflow, the method comprising: receiving a new node in the workspace; determining that the new node overlaps with one or more nodes; repositioning a set of nodes within a predetermined distance of the overlap, the set of nodes comprising the new node and the one or more nodes; determining that the new node still overlaps with the one or more nodes; and scaling down the set of nodes until there is no overlap.

One embodiments provides a system comprising: one or more processors; and one or more computer-readable media comprising instructions which, when executed by the one or more processors, cause the one or more processor to perform operations for automatically adjusting a workspace comprising a plurality of nodes for sustained workflow. The operations may comprise: receiving a new node in the workspace; determining that the new node overlaps with one or more nodes; repositioning a set of nodes within a predetermined distance of the overlap, the set of nodes comprising the new node and the one or more nodes; determining that the new node still overlaps with the one or more nodes; and scaling down the set of nodes until there is no overlap.

One embodiment provides one or more non-transitory computer-readable media comprising instructions which, when executed by one or more processors, cause the one or more processors to perform operations for automatically adjusting a workspace comprising a plurality of nodes for sustained workflow. The operations may comprise: receiving a new node in the workspace; determining that the new node overlaps with one or more nodes; repositioning a set of nodes within a predetermined distance of the overlap, the set of nodes comprising the new node and the one or more nodes; determining that the new node still overlaps with the one or more nodes; and scaling down the set of nodes until there is no overlap.

Additional objects and advantages of the disclosed embodiments will be set forth in part in the description that follows, and in part will be apparent from the description, or may be learned by practice of the disclosed embodiments. The objects and advantages of the disclosed embodiments will be realized and attained by means of the elements and combinations particularly pointed out in the appended claims.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosed embodiments, as claimed.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate various exemplary embodiments and together with the description, serve to explain the principles of the disclosed embodiments.

FIG. 1 shows an exemplary workspace of a node editor of a modeling application.

FIGS. 2A-2E illustrate sequential views of an exemplary self-adjusting workspace, according to one aspect of the present disclosure.

FIG. 3 is a flowchart illustrating an exemplary method of adjusting a workspace of a node editor, according to one aspect of the present disclosure.

FIGS. 4A-4C illustrate sequential views of an exemplary self-adjusting workspace during repositioning of nodes, according to one aspect of the present disclosure.

FIGS. 5A-5C illustrate sequential views of an exemplary self-adjusting workspace, in which overlaps between nodes remain after repositioning.

FIG. 6A shows an exemplary self-adjusting workspace, when a view of the workspace is panned out to show all nodes, according to one aspect of the present disclosure.

FIG. 6B shows an adjusted view of the exemplary self-adjusting workspace of FIG. 6A, according to one aspect of the present disclosure.

FIG. 7A shows an exemplary self-adjusting workspace including a plurality of nodes, according to one aspect of the present disclosure.

FIG. 7B shows a node density map that corresponds to the self-adjusting workspace of FIG. 7A.

 DETAILED DESCRIPTION OF EMBODIMENTS

The following embodiments describe systems and methods for 3D modeling process enhancement and, more particularly, for adjusting placement and scaling of nodes in a workspace of a node editor.

3D modeling software allows a user to navigate and inspect objects created in a virtual 3D space and work on small details as well as large scene elements without losing context. A node editor of such 3D modeling software may enable customization of object appearances using nodes and node connections, allowing a user to manipulate object properties to desired specifications. In general, a workspace of a node editor may be composed of i) nodes that represent computations and ii) connections between nodes to control how data flows through the nodes. When creating a complex object or scene, a workspace of the node editor may get clustered with nodes quickly, making visualization and/or addition of nodes more difficult and cumbersome. For instance, the user might have to manually move, group, and/or rescale existing nodes to make room for additional nodes within the workspace.

One solution to this problem is to either arrange existing nodes into node groups or fold the nodes away. Both of these options come with the disadvantage of requiring additional actions from the user to access the nodes again. Further, the node groups or folded areas may not necessarily be created in a logical and/or functional manner, making the resulting layout hard to interpret. Another solution is auto-layouting. This methodology also comes with a disadvantage of destroying the original setup or layout developed by the user, which may lead to a major interruption or confusion in the workflow.

The techniques contemplated in the present disclosure may alleviate or minimize the aforementioned problems. In general, the techniques discussed in the present disclosure provide an automated solution that does not destroy a user's original node layout, by repositioning and/or rescaling nodes based on the current scale and/or size of each node and/or distances from each other in the workspace. In one embodiment, in response to receiving a new node in a workspace, any overlap with existing nodes may be detected. If there is an overlap, a set of nodes within a vicinity of the overlap may be repositioned to even out node distribution around the new node. If there is still an overlap after repositioning, the set of nodes may be scaled down until no overlap exists. Alternatively, the set of nodes may be scaled without an initial repositioning, or the scaling may occur prior to any repositioning. Additionally, a view of the workspace may be adjusted to visually maintain the sizes of the nodes before they were scaled down (i.e., pre-scaling node sizes). By repositioning and/or rescaling nodes, the workspace may be able to hold as many nodes in as small an area as the user is comfortable with. The user may be allowed to zoom in and out of an area of interest within the workspace, for a better view and/or understanding of the node layout.

The subject matter of the present disclosure will now be described more fully hereinafter with reference to the accompanying drawings, which form a part hereof, and which show, by way of illustration, specific exemplary embodiments. An embodiment or implementation described herein as “exemplary” is not to be construed as preferred or advantageous, for example, over other embodiments or implementations; rather, it is intended to reflect or indicate that the embodiment(s) is/are “example” embodiment(s). Subject matter may be embodied in a variety of different forms and, therefore, covered or claimed subject matter is intended to be construed as not being limited to any exemplary embodiments set forth herein; exemplary embodiments are provided merely to be illustrative. Likewise, a reasonably broad scope for claimed or covered subject matter is intended. Among other things, for example, subject matter may be embodied as methods, devices, components, or systems. Accordingly, embodiments may, for example, take the form of hardware, software, firmware or any combination thereof. The following detailed description is, therefore, not intended to be taken in a limiting sense.

It should also be noted that all numeric values disclosed herein may have a variation of ±10% (unless a different variation is specified) from the disclosed numeric value. Further, all relative terms such as “about,” “substantially,” “approximately,” etc. are used to indicate a possible variation of ±10% (unless noted otherwise or another variation is specified).

Throughout the specification and claims, terms may have nuanced meanings suggested or implied in context beyond an explicitly stated meaning. Likewise, the phrase “in one embodiment” or “in some embodiments” as used herein does not necessarily refer to the same embodiment and the phrase “in another embodiment” as used herein does not necessarily refer to a different embodiment. It is intended, for example, that claimed subject matter include combinations of exemplary embodiments in whole or in part.

The terminology used below may be interpreted in its broadest reasonable manner, even though it is being used in conjunction with a detailed description of certain specific examples of the present disclosure. Indeed, certain terms may even be emphasized below; however, any terminology intended to be interpreted in any restricted manner will be overtly and specifically defined as such in this Detailed Description section.

Referring now to the appended drawings, FIG. 1 shows an exemplary workspace 100 of a node editor of a modeling application (e.g., a 3D modeling application). Using the node editor, a user may configure various visual properties of an object by creating appropriate nodes (e.g., node 110) and connections (e.g., connection 115) between inputs and outputs of those nodes. As more visual properties are configured and added, the workspace 100 may become cluttered with nodes and connections, making it difficult for the user to interpret the layout and/or place additional nodes in the limited space of the workspace 100. Further, the user may have to adjust the sizes of the existing nodes to make room for any future nodes, as well as the sizes of the nodes being added. The user may also need to place nodes in undesirable locations just to fit all required nodes in the limited space, making interpretation and placement of additional nodes even more cumbersome.

FIGS. 2A-2E illustrate sequential views of an exemplary self-adjusting workspace 200, according to one aspect of the present disclosure. The self-adjusting workspace 200 may be configured to alleviate the problems discussed above. For simplicity and ease of understanding, nodes depicted in FIGS. 2A-2E are illustrated merely as rectangles of varying sizes, and connections between the nodes are not shown. However, one of ordinary skill in the art will recognize that the nodes may be of varying types associated with corresponding operations, and may each include input(s) and/or output(s) enabling connections to and/or from other nodes in the workspace 200.

FIG. 2A shows a plurality of nodes that are present in the workspace 200, including nodes 20, 21, 22, 23, 24, 25, and 26. The sizes of the nodes may be different or the same. The nodes in FIG. 2A may represent a layout that is unaltered from a user-configured layout, or may represent a layout that has been altered automatically using the techniques of the present disclosure. The workspace 200 in FIG. 2A appears cluttered, making placement of additional nodes by the user at desirable locations difficult and cumbersome.

FIGS. 2B-2D depict partial views of the self-adjusting workspace 200, for the purpose of illustrating operations of the self-adjusting workspace 200 more clearly. FIG. 2B depicts a partial view of the self-adjusting workspace 200 of FIG. 2A prior to a new node being added within the workspace 200. The spaces between the nodes 20, 21, 22, 23, 24, 25, and 26 appear to be limited, which might cause an overlap when a new node is added proximate to any of these existing nodes. FIGS. 2C-2D depict operations of the self-adjusting workspace 200 when such a new node is added in the workspace 200. In FIGS. 2C-2D, in response to a user placing a new node 27 at the cluttered area of the workspace 200, certain existing nodes may be moved from their previous locations to make room for the new node 27. For example, the nodes 20, 21, 22, 23, 24, 25, and 26 may be repositioned, as illustrated by the changes in node positions from FIG. 2B to FIG. 2C, and from FIG. 2C to FIG. 2D. More specifically, the nodes 20, 21, 22, 23, 24, 25, and/or 26 may be moved or pushed away from the new node 27, in order to make room for the new node 27 and prevent the new node 27 and existing nodes from overlapping with each other. In some embodiments, node movement may be weighted such that closely-grouped nodes maintain their distances between each other, and nodes that are farther away are moved even farther away to provide space for the closely-grouped nodes to be repositioned. Existing node connections (e.g., the number of connections between a new node and an existing node) may also be considered in weighing the degree of movement for a node. From the user's point of view, the nodes may appear to push away from each other and away from where the overlap could have occurred, and even more so when the vicinity of the overlap is more densely populated with nodes (i.e., when a node density is large). In addition to repositioning, or alternatively, all or a subset of the new node 27 and existing nodes 20, 21, 22, 23, 24, 25, and 26 may be rescaled (e.g., scaled down), if an overlap still exists even after repositioning the nodes. In one embodiment, the rescaling may be based on the current scale and/or size of each node within a predetermined distance from the overlap. In some embodiments, the rescaling may be performed using node density (i.e., node weight) information associated with an area surrounding the new node 27 and existing nodes (e.g., an area within a predetermined distance from the overlap).

FIG. 2E depicts the self-adjusting workspace 200 after the nodes are rescaled. In addition to the nodes 20, 21, 22, 23, 24, 25, 26, and 27 being repositioned as explained above in reference to FIGS. 2B-2D, the node may be rescaled (e.g., scaled down) to eliminate further overlap between the nodes. All or a subset of the new node 27 and existing nodes 20, 21, 22, 23, 24, 25, and 26 may be rescaled (e.g., scaled down), if an overlap still exists after repositioning. In one embodiment, the rescaling may be based on the current scale and/or size of each node within a predetermined distance from the overlap. In an alternative or additional embodiment, the rescaling may be performed using node density (i.e., node weight) information associated with an area surrounding the new node 27 and existing nodes (e.g., an area within a predetermined distance from the overlap). For instance, nodes may be rescaled by evaluating a node density associated with a vicinity (i.e., local area that is within a predetermined distance) of the new node 27 or the overlap. In one embodiment, repositioning and/or rescaling of nodes may be performed such that distances between the nodes remain consistent. In another embodiment, distances between the nodes after repositioning and/or rescaling may be substantially proportional to the distances between the nodes prior to repositioning and/or rescaling. The repositioning and rescaling of the nodes will be explained in greater detail below.

FIG. 3 is a flowchart illustrating an exemplary method of adjusting a workspace of a node editor, according to one aspect of the present disclosure. Notably, method 300 may be performed by a modeling application comprising the node editor, to maintain a coherent, interpretable node layout in the workspace. At step 310, the modeling application may receive a new node in a workspace comprising one or more nodes (i.e., one or more existing nodes). For example, the new node may be added to the workspace when a user creates, drags, and drops the new node onto the workspace, or when a user triggers a function leading to creation of a new node. At step 320, the modeling application may determine whether the new node overlaps with one or more nodes in the workspace. If it is determined that the new node does not overlap with any node in the workspace, the method 300 may proceed to step 370 where the workspace adjustment process terminates. On the other hand, if it is determined that the new node overlaps with one or more nodes in the workspace, the method 300 may proceed to step 330.

At step 330, the modeling application may reposition a set of nodes within a vicinity of the overlap(s), in order to eliminate the overlap(s). The set of nodes may comprise the new node and the one or more nodes that overlap with the new node. The set of nodes may further comprise one or more other nodes in the workspace, including nodes that do not overlap with the new node. In general, a vicinity of an overlap may cover the area within close proximity from the detected overlap(s) such as, for example, the area within a predetermined distance from the detected overlap(s). In one embodiment, a vicinity of an overlap may comprise a circular area extending from a center point of the overlap(s). A radius of the circular area may be approximately twice a dimension of the new node, or approximately twice a dimension of a node that overlaps with the new node. The dimension of the new or existing node may be the length of a side of the node, which is usually rectangular-shaped. However, the radius of the circular area may be configured by a developer or an administrator of the modeling application to any specification using dimensions of nodes and/or any overlap(s) in the workspace. For example, a radius of the circular area may be approximately three times a dimension of the new node, or approximately three times a dimension of a node that overlaps with the new node. The set of nodes within the vicinity of the overlap may be repositioned such that the node distribution associated with the vicinity of the overlap is evened out (i.e., a local relaxation technique). In other words, the set of nodes may be moved away (i.e., “relaxed”) from the location of the overlap(s). In some embodiments, when the set of nodes in the vicinity of the overlap are pushed away from the overlap, certain nodes outside the vicinity of the overlap may also be pushed away, providing additional space for the set of nodes to be repositioned. In such a case, spaces between clusters of closely-grouped nodes may widen.

In an alternative or additional embodiment, repositioning may be based on the number of connection hops between the new node and each of the one or more nodes that overlap with the new node. The number of connection hops between two nodes may indicate the strength of relationship between the two nodes, or closeness between the two nodes. For example, the more the number of intervening nodes between two nodes, the weaker the relationship between the two nodes. In case of a weaker relationship, the “relaxation” of the node from the new node (i.e., the degree of movement away from the new node) may be more elastic, meaning the node may be pushed farther away from its previous position. In case of a stronger relationship, the “relaxation” of the node from the new node may be less elastic, meaning the node may be moved but may remain relatively close to its previous position. The relaxation technique based on the number of connection hops between nodes may be advantageous in preserving closely-related nodes within close proximity from each other, enabling the user to discern the strength of relationship between nodes based on distances between them and/or the extent of movement away from a new node.

FIGS. 4A-4C illustrate sequential views of an exemplary self-adjusting workspace 400 during repositioning of nodes, according to one aspect of the present disclosure. Notably, the operations illustrated in FIGS. 4A-4C may be performed by a modeling application comprising a node editor, to reposition nodes in response to identifying overlapping nodes in the workspace 400 upon a new node being added. In the example of FIG. 4A, the workspace 400 may initially contain nodes 40, 41, 42, 43, and 44. In FIG. 4B, a new node 45 may be added to the workspace 400. A user might add the new node 45 to a location that does not have enough space for the new node 45, creating an overlap with one or more of the existing nodes 40, 41, 42, 43, and 44. In the example of FIG. 4B, the new node 45 has been inserted at approximately the center point of the surrounding nodes 41, 42, 43, and 44, and the nodes 43 and 44 overlap with the new node 45. The modeling application may detect such an overlap, and may determine a vicinity of the overlap 400 based on the location of the overlap. As explained above, a vicinity of an overlap (e.g., the vicinity of the overlap 400) may comprise a circular area extending from a center point of the overlap, a radius of the circular area being, for example, approximately twice a dimension (e.g., a horizontal side, a vertical side, a diagonal line extending from a top right corner to a bottom left corner, etc.) of a new node (e.g., node 45) or an overlapping node (e.g., node 43, 44, or 45). However, a vicinity of an overlap may be configured to any suitable specification. In FIG. 4B, the vicinity of the overlap 400 completely encloses the new node 45 and the existing nodes 43 and 44, meaning entireties of the new node 45 and the existing nodes 43 and 44 are included within the vicinity of the overlap 400. The nodes that are completely enclosed in the vicinity of the overlap 400 may be part of “a set of nodes” mentioned throughout the present disclosure. Although the set of nodes depicted in FIG. 4B (e.g., nodes 43, 44, and 45) only includes overlapping nodes, the set of nodes may include one or more other nodes that do not overlap with the new node 45, depending on how parameters defining the vicinity of the overlap 500 have been configured by a developer or an administrator of the modeling application.

With continuing reference to FIG. 4B, the set of nodes comprising the new node 45 and the existing nodes 43 and 44 may be repositioned as discussed above in reference to step 330 of the method 300. The repositioned set of nodes are depicted in FIG. 4C.

Alternatively or additionally, the repositioning may consider the number of connection hops between the new node 45 and each of the nodes 43 and 45 that overlap with the new node 45. In FIG. 4B, the number of connection hops between the new node 45 and the node 43 is four, connecting the new node 45 to the node 43 via the intervening nodes 40, 41, and 42. The number of connection hops between the new node 45 and the node 44 is two, connecting the new node 45 to the node 44 via the intervening node 42. Based on the number of connection hops, the modeling application may determine that the connection or relationship between the new node 45 and the node 44 is stronger than the connection or relationship between the new node 45 and the node 43.

As explained above, a node whose connection with a new node is relatively weak may be moved farther away from its previous position, compared to repositioning of a node whose connection with the new node is relatively strong. For example, in FIG. 4C, the node 43 whose connection with the new node 45 is relatively weak has been moved farther away from its previous position shown in FIGS. 4A-4B, and the node 44 whose connection is relatively strong has been slightly moved from its previous position shown in FIGS. 4A-4B. It should be noted that a new node may also be repositioned from its initial location (e.g., the position at which the new node was dragged and dropped onto the workspace by a user, the position at which the new node was created in response to a user activating a function within the node editor, etc.). For example, in FIGS. 4B-4C, the new node 45 has been moved from its initial position shown in FIG. 4B to the position shown in FIG. 4C.

With renewed reference to FIG. 3, at step 340, the modeling application may determine whether the new node still overlaps with the one or more nodes in the workspace, even after repositioning the set of nodes at step 330. If it is determined that the new node no longer overlaps with the one or more nodes, the method 300 may proceed to step 370 where the workspace adjustment process terminates. On the other hand, if it is determined that the new node still overlaps with the one or more nodes, the method 300 may proceed to step 350. As an example, FIGS. 5A-5C illustrate sequential views of an exemplary self-adjusting workspace 500, in which overlaps between multiple nodes still exist after repositioning. In FIG. 5A, the workspace 500 may initially contain multiple nodes, including nodes 50, 51, 52, and 53. Subsequently, a new node 54 may be added to the workspace 500 as shown in FIG. 5B. A user might add the new node 54 to a location that does not have enough space for the new node 54, creating an overlap with one or more of the existing nodes 50, 51, 52, and 53. The modeling application may detect the overlap(s), and may reposition the nodes based on node distribution and/or the number of connection hops between the new node 54 and each of the overlapping existing nodes 50, 51, 52, and 53. The repositioned nodes 50, 51, 52, and 53 are depicted in FIG. 5C. As shown in FIG. 5C, repositioning of the nodes might not completely eliminate the overlap(s) in the workspace 500. In such a case, the modeling application may perform additional operations to eliminate the overlap(s), such as by rescaling or scaling down certain nodes in the workspace 500. The rescaling operation is explained in greater detail below.

Referring back to FIG. 3, at step 350, the modeling application may scale down (i.e., rescale) the set of nodes until there is no overlap. As explained above, the set of nodes may comprise the one or more nodes that overlap with the new node, as well as the new node that is added to the workspace. The set of nodes may further comprise one or more other nodes that do not overlap with the new node. In general, the set of nodes may be scaled down to the point where no overlap occurs between the nodes, and such rescaling may be performed based on the current scale and/or size of each node within a predetermined distance of the overlap. Parameters defining the local area in which the nodes to be rescaled are positioned may be configured by a developer or an administrator of the modeling application. In some embodiments, a pair of nodes may still be considered to be overlapping when the rectangular windows of the nodes merely “touch” each other, meaning the nodes are placed exactly adjacent to each other and one node does not necessarily obscure a portion of the other node. In such a case, the set of nodes may be scaled down do the point where a certain distance or gap is achieved between the nodes, to allow for connections between the nodes to be readily recognizable by clearing the area immediately outside the periphery of each node. The exact distance or the amount/size of the gap required between two nodes, to be considered non-overlapping, may depend on dimensions of various graphical user interface (GUI) elements used in the node editor.

In an alternative or additional embodiment, the set of nodes may be rescaled based on a node density map of the workspace. A node density map may be generated based on the location and density/weight of each node included in the workspace. The effective density or weight of a node may be calculated based on its size and current scale. Each node may thus add a fraction to the total density/weight associated with the workspace, or a portion of the workspace. FIG. 7A shows an exemplary self-adjusting workspace 700 including a plurality of nodes, and FIG. 7B shows a node density map that corresponds to the workspace 700 shown in FIG. 7A. In areas where nodes are densely populated, which may be identified from the node density map, the nodes may be scaled down to relatively smaller sizes compared to areas where nodes are more sparsely populated or scattered. In general, the scale or the size of a node may be inversely proportional to the node density or weight associated with the local area surrounding the node (e.g., a vicinity of an overlap, an area within a predetermined distance from the node/overlap). Parameters defining the local area of a node may be configured by a developer or an administrator of the modeling application.

It should be noted that, the area enclosing the nodes to be repositioned may be within a first predetermined distance from the point of overlap detected at step 320, and the area enclosing the nodes to be rescaled may be within a second predetermined distance from the point of overlap detected at step 340. In one embodiment, the first predetermined distance and the second predetermined distance may be the same. In other embodiments, the first predetermined distance and the second predetermined distance may be different. As explained above, a developer or an administrator may configure parameters defining the area in which the nodes to be repositioned or rescaled exist.

To prevent differences in node scale while using the node editor, which might irritate the end user, the modeling application may adjust scaling as the user pans to have the nodes in the user's field of view at the same scale. In one embodiment, the action of scaling nodes to the same scale may be performed by the modeling application in response to determining that the workspace is being scrolled by the user (i.e., in response to the user zooming in on a particular area of the workspace). In some embodiments, the actions of panning (e.g., zooming in) and scaling nodes to the same sale may be performed automatically by the modeling application. As an example, FIG. 6A shows an exemplary self-adjusting workspace 600, when a view of the workspace is panned out to show all nodes. Notably, when the view is completely panned out, the nodes may be shown at their true scales, all or some of which may be representative of any adjustment made upon a new node being added to the workspace. However, the user might only be interested in a subset of the nodes at a particular point in time, the subset of nodes being in close proximity to a new node or any node that the user might be interested in. For example, upon the user adding the node 64, the user might be interested in the surrounding nodes 60, 61, 62, 63, and 65, as one or more of those nodes are likely to be connected to the new node 64. Therefore, the modeling application may be configured to adjust the view to zoom in on the nodes 60, 61, 62, 63, 64, and 65, upon the new node 64 being added to the workspace and the nodes in proximity to the new node 64 being rescaled. The area containing the nodes 60, 61, 62, 63, 64, and 65 to which the view may be adjusted is shown as an area of interest 650 in FIG. 6A. FIG. 6B shows an adjusted view of the exemplary self-adjusting workspace 600 upon, for example, a new node being added. As explained above, the modeling application may adjust the view to zoom in on the area of interest 650 containing nodes 60, 61, 62, 63, 64, and 65. In addition to zooming in, the modeling application may also adjust the sizes of the nodes 60, 61, 62, 63, 64, and 65 to their pre-scaling sizes, in order maintain the nodes at a same scale for user convenience and improved workflow. The nodes 60, 61, 62, 63, 64, and 65 are thus shown at the same scale in the adjusted view illustrated in FIG. 6B. If the user wants to view or work on nodes positioned outside the area of interest 650, the user may be able to pan out to see the entire workspace 600, or a portion of the workspace 600 that is larger than the area of interest 650, either of which may show the nodes at their true scales depending on a pre-defined specification.

With renewed reference to FIG. 3, to maintain nodes that the user might be interested in at the same scale as explained above in reference to FIGS. 6A-6B, once the set of nodes are scaled down at step 350, the modeling application may adjust a view of the workspace to visually maintain pre-scaling sizes of the set of nodes at step 360. The view may be adjusted by zooming in on the nodes that are in close proximity to the new node, which may be the area of interest to the user. Parameters defining the degree to which the view is zoomed in, or the area of interest to which the view is adjusted, may be configured by a developer or an administrator of the modeling application. When the view is adjusted, the nodes visible within the adjusted view may also be adjusted to their pre-scaling node sizes. In one embodiment, the adjusted view may cover the vicinity of the overlap determined at step 330. In other embodiments, the adjusted view may cover an area larger than the vicinity of the overlap, or an area smaller than the vicinity of the overlap. Therefore, the adjusted view may include nodes that are outside the vicinity of the overlap, and the nodes outside the vicinity of the overlap may also be scaled back to their pre-scaling node sizes. The pre-scaling node size of a node may be determined based on a multiplicative inverse of the scale change at step 350. If the user wants to view or work on nodes positioned outside the area of interest represented by the adjusted view, the user may be able to pan out to see the entire workspace, or a portion of the workspace that is larger than the area of interest, either of which may show the nodes at their true scales.

Embodiments of the present disclosure and all of the functional operations described in this specification can be implemented in digital electronic circuitry, or in computer software, firmware, or hardware, including the structures disclosed in this specification and their structural equivalents, or in combinations of one or more of them. Embodiments of the present disclosure can be implemented as one or more computer program products, e.g., one or more modules of computer program instructions encoded on a computer readable medium for execution by, or to control the operation of, data processing apparatus. The computer readable medium can be a machine-readable storage device, a machine-readable storage substrate, a memory device, a composition of matter effecting a machine-readable propagated signal, or a combination of one or more of them. The term “data processing apparatus” encompasses all apparatus, devices, and machines for processing data, including by way of example a programmable processor, a computer, or multiple processors or computers. The apparatus can include, in addition to hardware, code that creates an execution environment for the computer program in question, e.g., code that constitutes processor firmware, a protocol stack, a database management system, an operating system, or a combination of one or more of them. A propagated signal is an artificially generated signal, e.g., a machine-generated electrical, optical, or electromagnetic signal that is generated to encode information for transmission to suitable receiver apparatus.

A computer program (also known as a program, software, software application, script, or code) can be written in any form of programming language, including compiled or interpreted languages, and it can be deployed in any form, including as a stand-alone program or as a module, component, subroutine, or other unit suitable for use in a computing environment. A computer program does not necessarily correspond to a file in a file system. A program can be stored in a portion of a file that holds other programs or data (e.g., one or more scripts stored in a markup language document), in a single file dedicated to the program in question, or in multiple coordinated files (e.g., files that store one or more modules, sub programs, or portions of code). A computer program can be deployed to be executed on one computer or on multiple computers that are located at one site or distributed across multiple sites and interconnected by a communication network.

The processes and logic flows described in this specification can be performed by one or more programmable processors executing one or more computer programs to perform functions by operating on input data and generating output. The processes and logic flows can also be performed by, and apparatus can also be implemented as, special purpose logic circuitry, e.g., an FPGA (field programmable gate array) or an ASIC (application specific integrated circuit).

Processors suitable for the execution of a computer program include, by way of example, both general and special purpose microprocessors, and any one or more processors of any kind of digital computer. Generally, a processor will receive instructions and data from a read only memory or a random access memory or both. The essential elements of a computer are a processor for performing instructions and one or more memory devices for storing instructions and data. Generally, a computer will also include, or be operatively coupled to receive data from or transfer data to, or both, one or more mass storage devices for storing data, e.g., magnetic, magneto optical disks, or optical disks. However, a computer need not have such devices. Moreover, a computer can be embedded in another device, e.g., a tablet computer, a mobile telephone, a personal digital assistant (PDA), a mobile audio player, a Global Positioning System (GPS) receiver, to name just a few. Computer readable media suitable for storing computer program instructions and data include all forms of non-volatile memory, media and memory devices, including by way of example semiconductor memory devices, e.g., EPROM, EEPROM, and flash memory devices; magnetic disks, e.g., internal hard disks or removable disks; magneto optical disks; and CD ROM and DVD-ROM disks. The processor and the memory can be supplemented by, or incorporated in, special purpose logic circuitry.

To provide for interaction with a user, embodiments of the present disclosure can be implemented on a computer having a display device, e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor, for displaying information to the user and a keyboard and a pointing device, e.g., a mouse or a trackball, by which the user can provide input to the computer. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback, e.g., visual feedback, auditory feedback, or tactile feedback; and input from the user can be received in any form, including acoustic, speech, or tactile input.

Embodiments of the present disclosure can be implemented in a computing system that includes a back end component, e.g., as a data server, or that includes a middleware component, e.g., an application server, or that includes a front end component, e.g., a client computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the present disclosure, or any combination of one or more such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication, e.g., a communication network. Examples of communication networks include a local area network (“LAN”) and a wide area network (“WAN”), e.g., the Internet.

The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.

While this specification contains many specifics, these should not be construed as limitations on the scope of the present disclosure or of what may be claimed, but rather as descriptions of features specific to particular embodiments of the present disclosure. Certain features that are described in this specification in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable subcombination. Moreover, although features may be described above as acting in certain combinations and even initially claimed as such, one or more features from a claimed combination can in some cases be excised from the combination, and the claimed combination may be directed to a subcombination or variation of a subcombination.

Similarly, while operations are depicted in the drawings in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. In certain circumstances, multitasking and parallel processing may be advantageous. Moreover, the separation of various system components in the embodiments described above should not be understood as requiring such separation in all embodiments, and it should be understood that the described program components and systems can generally be integrated together in a single software product or packaged into multiple software products.

Claims

1. A computer-implemented method of automatically adjusting a workspace comprising a plurality of nodes for sustained workflow, the method comprising:

receiving a new node in the workspace;
determining that the new node overlaps with one or more nodes;
repositioning a set of nodes within a predetermined distance of the overlap, the set of nodes comprising the new node and the one or more nodes;
determining that the new node still overlaps with the one or more nodes;
determining a weight for each node within a second predetermined distance of the overlap;
scaling down each node in the set of nodes based on the weight until there is no overlap, and
adjusting a view of the workspace to visually maintain a pre-scaling relative node size of each of the new node and the one or more nodes.

2. The computer-implemented method of claim 1, wherein the set of nodes further comprises one or more other nodes.

3. The computer-implemented method of claim 1, wherein the workspace comprises a workspace of a node editor of an object modeling application.

4. The computer-implemented method of claim 1, wherein each of the plurality of nodes is associated with one or more properties of an object.

5. The computer-implemented method of claim 1, wherein the repositioning is based at least in part on distances between the set of nodes.

6. The computer-implemented method of claim 1, wherein the repositioning is based at least in part on a number of connection hops between the new node and each of the one or more nodes.

7. The computer-implemented method of claim 1, wherein the scaling further comprises:

determining a size of each node within the second predetermined distance of the overlap; and
scaling based on the size of each node within the second predetermined distance of the overlap.

8. The computer-implemented method of claim 1, wherein the predetermined distance of the overlap comprises a circular area extending from a center point of the overlap, a radius of the circular area being at least twice the dimension of at least one of the new node and the one or more nodes.

9. The computer-implemented method of claim 1, further comprising:

determining that the workspace is being scrolled; and
in response to determining that the workspace is being scrolled, adjusting a view of the workspace to visually maintain pre-scaling sizes of the set of nodes, wherein the pre-scaling sizes are sizes of the set of nodes prior to being scaled down.

10. The computer-implemented method of claim 9, wherein the adjusting comprises:

zooming in on an area of interest; and
displaying the set of nodes at the pre-scaling sizes.

11. The computer-implemented method of claim 1, wherein the weight of nodes is based on a density map.

12. A system comprising:

one or more processors;
one or more non-transitory processor readable storage devices comprising instructions which, when executed by the one or more processors, cause the one or more processor to perform operations for automatically adjusting a workspace comprising a plurality of nodes for sustained workflow, the operations comprising: receiving a new node in the workspace; determining that the new node overlaps with one or more nodes; repositioning a set of nodes within a predetermined distance of the overlap, the set of nodes comprising the new node and the one or more nodes; determining that the new node still overlaps with the one or more nodes; determining a weight of each node within a second predetermined distance of the overlap; scaling down the set of nodes based on the weight until there is no overlap, and adjusting a view of the workspace to visually maintain a pre-scaling relative node size of each of the new node and the one or more nodes.

13. The system of claim 12, wherein the set of nodes further comprises one or more other nodes.

14. The system of claim 12, wherein the workspace comprises a workspace of a node editor of an object modeling application.

15. The system of claim 12, wherein the repositioning is based at least in part on distances between the set of nodes.

16. The system of claim 12, wherein the repositioning is based at least in part on a number of connection hops between the new node and each of the one or more nodes.

17. The system of claim 12, wherein the scaling further comprises:

determining a size of each node within second predetermined distance of the overlap; and
scaling based on the size of each node within the second predetermined distance of the overlap.

18. The system of claim 12, wherein the predetermined distance of the overlap comprises a circular area extending from a center point of the overlap, a radius of the circular area being at least twice the dimension of at least one of the new node and the one or more nodes.

19. The system of claim 12, the operations further comprising:

adjusting a view of the workspace to visually maintain pre-scaling sizes of the set of nodes, wherein the pre-scaling sizes are sizes of the set of nodes prior to being scaled down.

20. The system of claim 19, wherein the adjusting comprises:

zooming in on an area of interest; and
displaying the set of nodes at the pre-scaling sizes.

21. One or more non-transitory computer-readable media comprising instructions which, when executed by one or more processors, cause the one or more processors to perform operations for automatically adjusting a workspace comprising a plurality of nodes for sustained workflow, the operations comprising:

receiving a new node in the workspace;
determining that the new node overlaps with one or more nodes;
repositioning a set of nodes within a predetermined distance of the overlap, the set of nodes comprising the new node and the one or more nodes;
determining that the new node still overlaps with the one or more nodes;
determining a weight of each node within a second predetermined distance of the overlap;
scaling down the set of nodes based on the weight until there is no overlap, and
adjusting a view of the workspace to visually maintain a pre-scaling relative node size of each of the set of nodes.
Referenced Cited
U.S. Patent Documents
4730186 March 8, 1988 Koga et al.
4963967 October 16, 1990 Orland et al.
5040081 August 13, 1991 McCutchen
5060135 October 22, 1991 Levine
5086495 February 4, 1992 Gray et al.
5485563 January 16, 1996 Fisher
5519828 May 21, 1996 Rayner
5555357 September 10, 1996 Fernandes
5623612 April 22, 1997 Haneda et al.
5664132 September 2, 1997 Smith
5745113 April 28, 1998 Jordan
5828360 October 27, 1998 Anderson et al.
5933153 August 3, 1999 Deering et al.
5936671 August 10, 1999 Van Beek et al.
5973691 October 26, 1999 Servan-Schreiber
5982909 November 9, 1999 Erdem et al.
5986662 November 16, 1999 Argiro et al.
6108006 August 22, 2000 Hoppe
6144378 November 7, 2000 Lee et al.
6259458 July 10, 2001 Theisen
6373488 April 16, 2002 Gasper
6389173 May 14, 2002 Suzuki et al.
6448987 September 10, 2002 Easty et al.
6452875 September 17, 2002 Lee et al.
6546558 April 8, 2003 Taguchi
6549219 April 15, 2003 Selker
6629065 September 30, 2003 Gadh
6728682 April 27, 2004 Fasciano
6771263 August 3, 2004 Behrens et al.
6839462 January 4, 2005 Kitney et al.
6879322 April 12, 2005 Iida
6888916 May 3, 2005 Launay et al.
6973200 December 6, 2005 Tanaka et al.
6993399 January 31, 2006 Covell et al.
7290704 November 6, 2007 Ball et al.
7372472 May 13, 2008 Bordeleau et al.
7401731 July 22, 2008 Pletz et al.
7413113 August 19, 2008 Zhu
7423645 September 9, 2008 Dougherty et al.
7439975 October 21, 2008 Hsu et al.
7487170 February 3, 2009 Stevens
7512886 March 31, 2009 Herberger et al.
7584152 September 1, 2009 Gupta et al.
7603623 October 13, 2009 Lengeling et al.
7668243 February 23, 2010 Ho et al.
7692724 April 6, 2010 Arora et al.
7701445 April 20, 2010 Inokawa et al.
7730429 June 1, 2010 Kruse et al.
7770125 August 3, 2010 Young
7831521 November 9, 2010 Ball et al.
7949946 May 24, 2011 Mollicone
8103545 January 24, 2012 Ramer et al.
8140389 March 20, 2012 Altberg et al.
8161396 April 17, 2012 Barber
8205148 June 19, 2012 Sharpe et al.
8336770 December 25, 2012 Grillion
8345046 January 1, 2013 Norrby
8370761 February 5, 2013 Good
8375329 February 12, 2013 Drayton et al.
8413040 April 2, 2013 O'Dell-Alexander
8519979 August 27, 2013 Smith
8560449 October 15, 2013 Sears
8601366 December 3, 2013 Saltwell
8659621 February 25, 2014 Stiglitz
8667406 March 4, 2014 Thakur
8698806 April 15, 2014 Kunert et al.
8793599 July 29, 2014 Lajoie
8850335 September 30, 2014 Eldridge
9035949 May 19, 2015 Oberheu
9038001 May 19, 2015 Jetter
9158508 October 13, 2015 Eldridge
9223488 December 29, 2015 Lajoie
9449647 September 20, 2016 Sharpe et al.
9478033 October 25, 2016 Sharpe et al.
9734608 August 15, 2017 Grealish
9740368 August 22, 2017 Love
9766787 September 19, 2017 Danton
9804747 October 31, 2017 Schmitlin
9911211 March 6, 2018 Damaraju
10434717 October 8, 2019 Boettcher et al.
11321904 May 3, 2022 Kniemeyer
20020094135 July 18, 2002 Caspi et al.
20020122113 September 5, 2002 Foote
20020123938 September 5, 2002 Yu et al.
20030146915 August 7, 2003 Brook et al.
20030160944 August 28, 2003 Foote et al.
20030179234 September 25, 2003 Nelson
20030179740 September 25, 2003 Baina et al.
20040049739 March 11, 2004 McArdle
20040148159 July 29, 2004 Crockett et al.
20040170392 September 2, 2004 Lu et al.
20050046889 March 3, 2005 Braudaway
20050091599 April 28, 2005 Yamakado
20050162395 July 28, 2005 Unruh
20050165840 July 28, 2005 Pratt et al.
20050192956 September 1, 2005 Evans
20050199714 September 15, 2005 Brandt et al.
20060008247 January 12, 2006 Minami et al.
20060078305 April 13, 2006 Arora et al.
20060098007 May 11, 2006 Rouet et al.
20060121436 June 8, 2006 Kruse
20060123445 June 8, 2006 Sullivan et al.
20060150072 July 6, 2006 Salvucci
20060150215 July 6, 2006 Wroblewski
20060212704 September 21, 2006 Kirovski et al.
20060290695 December 28, 2006 Salomie
20070002047 January 4, 2007 Desgranges et al.
20070036403 February 15, 2007 Albertson
20070075998 April 5, 2007 Cook et al.
20070100773 May 3, 2007 Wallach
20070162844 July 12, 2007 Woodall
20070189708 August 16, 2007 Lerman et al.
20070230765 October 4, 2007 Wang et al.
20070248321 October 25, 2007 Hamada
20070248322 October 25, 2007 Hamada
20070256029 November 1, 2007 Maxwell
20070257909 November 8, 2007 Kihslinger
20080005130 January 3, 2008 Logan et al.
20080012859 January 17, 2008 Saillet
20080021787 January 24, 2008 Mackouse
20080033880 February 7, 2008 Fiebiger et al.
20080079851 April 3, 2008 Stanger et al.
20080082510 April 3, 2008 Wang et al.
20080099552 May 1, 2008 Grillion
20080117204 May 22, 2008 Thom
20080150937 June 26, 2008 Lundstrom et al.
20080162577 July 3, 2008 Fukuda et al.
20080177663 July 24, 2008 Gupta et al.
20080256448 October 16, 2008 Bhatt
20080301341 December 4, 2008 Mosek et al.
20080304814 December 11, 2008 Fujii
20080306790 December 11, 2008 Otto et al.
20080313565 December 18, 2008 Albertson
20090034940 February 5, 2009 Hamada
20090063312 March 5, 2009 Hurst
20090079742 March 26, 2009 Albertson
20090087161 April 2, 2009 Roberts et al.
20090100333 April 16, 2009 Xiao
20090157519 June 18, 2009 Bishop et al.
20090167942 July 2, 2009 Hoogenstraaten et al.
20090171683 July 2, 2009 Hoyos et al.
20090192904 July 30, 2009 Patterson et al.
20090198614 August 6, 2009 De Ruiter et al.
20090199123 August 6, 2009 Albertson
20090228786 September 10, 2009 Danton
20090231337 September 17, 2009 Carr et al.
20090254864 October 8, 2009 Whittington et al.
20090279453 November 12, 2009 Yeh et al.
20090318800 December 24, 2009 Gundel et al.
20090319948 December 24, 2009 Stannard
20100050083 February 25, 2010 Axen et al.
20100050102 February 25, 2010 Baba
20100053215 March 4, 2010 Coldicott
20100058161 March 4, 2010 Coldicott
20100058162 March 4, 2010 Coldicott
20100063903 March 11, 2010 Whipple et al.
20100083077 April 1, 2010 Paulsen
20100146393 June 10, 2010 Land et al.
20100153841 June 17, 2010 Haug, III
20100183280 July 22, 2010 Beauregard et al.
20100185985 July 22, 2010 Chmielewski et al.
20100192101 July 29, 2010 Chmielewski et al.
20100192102 July 29, 2010 Chmielewski et al.
20100211860 August 19, 2010 O'Dell-Alexander
20100228669 September 9, 2010 Karim
20100333030 December 30, 2010 Johns
20110161873 June 30, 2011 Murakami
20110169825 July 14, 2011 Ishiyama
20120020585 January 26, 2012 Okuhara
20120081389 April 5, 2012 Dilts
20120246596 September 27, 2012 Ording
20120290609 November 15, 2012 Britt
20120293558 November 22, 2012 Dilts
20130073500 March 21, 2013 Szatmary
20130093787 April 18, 2013 Fulks
20130132895 May 23, 2013 Nemeth
20130151413 June 13, 2013 Sears
20130191775 July 25, 2013 Lawson
20130227427 August 29, 2013 Mockli
20130232442 September 5, 2013 Groth
20130328870 December 12, 2013 Grenfell
20140101605 April 10, 2014 Udvardy
20140132603 May 15, 2014 Raghoebardayal
20140164989 June 12, 2014 Kuh
20140214825 July 31, 2014 Zhang
20140317500 October 23, 2014 Kim
20140354650 December 4, 2014 Singh
20140359525 December 4, 2014 Weiner
20140372894 December 18, 2014 Pandy
20150106755 April 16, 2015 Moore
20150134095 May 14, 2015 Hemani et al.
20150149314 May 28, 2015 Sears
20150161595 June 11, 2015 Sears
20150279071 October 1, 2015 Xin
20150331968 November 19, 2015 Crocker
20150339379 November 26, 2015 Inagaki
20160041727 February 11, 2016 Choi
20160103793 April 14, 2016 Fang
20160216872 July 28, 2016 Dilts
20160261544 September 8, 2016 Conover
20170078504 March 16, 2017 Nagata
20170116315 April 27, 2017 Xiong
20170371530 December 28, 2017 Vranjes
20180048661 February 15, 2018 Bird
20180108164 April 19, 2018 Dilts
20180307754 October 25, 2018 Somlai-Fischer
20190005115 January 3, 2019 Warner
20190163835 May 30, 2019 Scheideler
20190258693 August 22, 2019 Lawrence
20190311219 October 10, 2019 Alabdulmohsin
20190379700 December 12, 2019 Canzanese, Jr.
20200137195 April 30, 2020 Lipke
20210065424 March 4, 2021 Kniemeyer
20210272327 September 2, 2021 Wang
20210286510 September 16, 2021 Tyler
20210286534 September 16, 2021 Mulholland
20220068022 March 3, 2022 Kemmler
20220068036 March 3, 2022 Ng
20220101065 March 31, 2022 Adeniran
20220179883 June 9, 2022 Biernacki
20220308740 September 29, 2022 Kawano
Foreign Patent Documents
0916374 May 1999 EP
2230666 September 2010 EP
2008305241 December 2008 JP
WO0139130 May 2001 WO
WO2004040576 May 2004 WO
WO2009042858 April 2009 WO
WO2010034063 April 2010 WO
WO2010068175 June 2010 WO
WO2010138776 December 2010 WO
WO2016179401 November 2016 WO
Other references
  • Shrstha et al., “Synchronization of Multi-Camera Video Recordings Based on Audio”, MM '07: Proceedings of the 15th ACM international conference on Multimedia, Sep. 2007, Augsburg, Bavaria, Germany, pp. 545-548, 5 pages. https://doi.org/10.1145/1291233.1291367.
  • Toklu et al., “Semi-automatic video object segmentation in the presence of occlusion”, Jun. 2000, IEEE Transactions on Circuits and Systems for Video Technology, vol. 10, iss. 624-629, 3 pages.
  • Toklu et al., “Two-dimensional triangular mesh-based mosaicking for object tracking in the presence of occlusion”, Jan. 10, 1997, Proc. SPIE, Visual Communications and Image Processing '97, vol. 3024, p. 328-337, 11 pages.
  • Toklu et al., “Tracking Motion and Intensity Variations Using Hierarchical 2-D Mesh Modeling for Synthetic Object Transfiguration”, Nov. 1996, Graphical Models and Image Processing, vol. 58, No. 6, p. 553-573, 21 pages.
  • Jain et al., “Non-Rigid Spectral Correspondence of Triangle Meshes”, Apr. 5, 2007, International Journal of Shape Modeling, 25 pages.
  • Toklu et al., “2-D mesh-based tracking of deformable objects with occlusion”, Sep. 19, 1996, Proceedings of International Conference on Image Processing, 1996, vol. 1, p. 933-936, 3 pages.
  • Zhao et al., “An object tracking algorithm based on occlusion mesh model”, 2002, Proceedings of International Conference on Machine Learning and Cybernetics, 2002, vol. 1, p. 288-292, 3 pages.
  • Altunbasak et al., “Occlusion-adaptive 2-D mesh tracking”, May 10, 1996, Conference Proceedings ICASSP-96, vol. 4, p. 2108-2111.
  • Tekalp et al., “Face and 2-D mesh animation in MPEG-4”, Jan. 2000, Signal Processing: Image Communication, vol. 15, issue 4-5, p. 387-421. https://doi.org/10.1016/S0923-5965(99)00055-7.
  • Shewchuk, “Triangle: Engineering a 2D quality mesh generator and Delaunay triangulator”, 1996, Applied Computational Geometry towards Geometric Engineering Lecture Notes in Computer Science, 1996, vol. 1148, 11 pages.
  • Dobashi et al., Interactive Rendering method for Displaying Shafts of Light, Proceedings Computer Graphics and Applications; Oct. 2000, pp. 31-37, 435, 3 pages. DOI:10.1109/PCCGA.2000.883864.
  • Li et al., Unified Volumes for Light Shaft and Shadow with Scattering, 2007 10th IEEE International Conference on Computer-Aided Design and Computer Graphics, Oct. 2007, pp. 161-166.
  • Akenine-Moller, T., et al., Real-Time Rendering, (Second Edition, A. K. Peters, Ltd., Wellesley, MA), (202), pp. 158, 315-316.
  • Herndon, K. P., et al., “Interactive Shadows”, UIST: Proceedings of the Fifth Annual ACM Symposium on User Interface Software and Technology, (Nov. 15-18, 1992), (1992), 1-6.
  • Loscos, C., et al., “Real-Time Shadows for Animated Crowds in Virtual Cities”, VRST 2001. Proceedings of the ACM Symposium on Virtual Reality Software and Technology, (Nov. 15-17, 2001, Banff, Alberta, Canada), (2001), 85-92.
  • Woo, A., et al., “A Survey of Shadow Algorithms”, IEEE Computer Graphics & Applications, (Nov. 1990), 31 pages.
  • Bregler, Christoph et al., “Video Rewrite: Driving Visual Speech with Audio”, ACM Siggraph 97, Proceedings of the 24th Annual Conference on Computer Graphics and Interactive Techniques, 1997, ISBN: 0-89791-896-7, pp. 1-8.
  • Haitsma, J. et al., “A Highly Robust Audio Fingerprinting System”, IRCAM, 2002, 9 pages.
  • Held M, Palfrader P. Skeletal structures for modeling generalized chamfers and fillets in the presence of complex miters. Computer-Aided Design and Applications. Jan. 1, 2019;16(4):620-7, 8 pages.
  • Palfrader, P., Weighted Skeletal Structures in Theory and Practice (Doctoral dissertation, University of Salzburg), 111 pages.
  • Martin Held et al., ‘Straight Skeletons and Mitered Offsets of Polyhedral Terrains in 3D’, Computer-Aided Design and Applications, vol. 16, No. 4, 2019, pp. 611-619, Jul. 9, 2018, pp. 611-617.
  • Gill Barequet et al., ‘Straight Skeletons of Three-Dimensional Polyhedra’, arXiv:0805.0022v1, Apr. 30, 2008, pp. 1-11.
  • “Alaric: Euronet Worldwide to implement Alarics Fractals fraud detection solution; Fractals will provide a comprehensive fraud solution for the prevention and detection of fraudulent transactions”, M2 Presswire [Coventry],Nov. 7, 2006, pp. 1-2.
Patent History
Patent number: 11714928
Type: Grant
Filed: Feb 27, 2020
Date of Patent: Aug 1, 2023
Patent Publication Number: 20210271784
Assignee: MAXON COMPUTER GMBH (Friedrichsdorf)
Inventor: Björn Dirk Marl (Friedrichsdorf)
Primary Examiner: Charles L Beard
Application Number: 16/802,734
Classifications
Current U.S. Class: Thumbnail Or Scaled Image (715/838)
International Classification: G06F 30/12 (20200101); G06T 19/20 (20110101); G06F 30/18 (20200101);